How do you handle sequence padding and truncation in text-based generative AI

Question

With the help of code example can you explain how do you handle sequence padding and truncation in text-based generative AI?

Answer 1

In text-based generative AI, sequence padding and truncation are handled to ensure input sequences have consistent lengths. Here is the code snippet you can refer to,  which uses Hugging Face's transformers library:

In the above code, we are using the following key components:

• padding="max_length": Pads shorter sequences to the specified max_length.
• truncation=True: Truncates sequences longer than max_length.
• attention_mask: Indicates which tokens are padding (0) and real (1).

Hence, by referring to the above, you can handle sequence padding and truncation in text-based generative AI.